A data center may be defined as a location, e.g., room, that houses computer systems arranged in a number of racks. A standard rack, e.g., electronics cabinet, is defined as an Electronics Industry Association (EIA) enclosure, 78 in. (2 meters) high, 24 in. (0.61 meter) wide and 30 in. (0.76 meter) deep. These racks are configured to house a number of computer systems, e.g., about forty (40) systems, with future configurations of racks being designed to accommodate up to eighty (80) systems. The computer systems typically include a number of components, e.g., one or more of printed circuit boards (PCBs), mass storage devices, power supplies, processors, micro-controllers, semi-conductor devices, and the like, that may dissipate relatively significant amounts of heat during the operation of the respective components. For example, a typical computer system comprising multiple microprocessors may dissipate approximately 250 W of power. Thus, a rack containing forty (40) computer systems of this type may dissipate approximately 10 KW of power.
The power required to transfer the heat dissipated by the components in the racks to the cool air contained in the data center is generally equal to about 10 percent of the power needed to operate the components. However, the power required to remove the heat dissipated by a plurality of racks in a data center is generally equal to about 50 percent of the power needed to operate the components in the racks. The disparity in the amount of power required to dissipate the various heat loads between racks and data centers stems from, for example, the additional thermodynamic work needed in the data center to cool the air. In one respect, racks are typically cooled with fans that operate to move cooling fluid, e.g., air, cooling fluid, etc., across the heat dissipating components; whereas, data centers often implement reverse power cycles to cool heated return air. The additional work required to achieve the temperature reduction, in addition to the work associated with moving the cooling fluid in the data center and the condenser, often add up to the 50 per cent power requirement. As such, the cooling of data centers presents problems in addition to those faced with the cooling of the racks.
Conventional data centers are typically cooled by operation of one or more air conditioning units. For example, compressors of air conditioning units typically consume a minimum of about thirty (30) percent of the required operating energy to sufficiently cool the data centers. The other components, e.g., condensers, air movers (fans), etc., typically consume an additional twenty (20) percent of the required total operating energy. As an example, a high density data center with 100 racks, each rack having a maximum power dissipation of 10 KW, generally requires 1 MW of cooling capacity. Air conditioning units with a capacity of 1 MW of heat removal generally requires a minimum of 300 KW input compressor power in addition to the power needed to drive the air moving devices, e.g., fans, blowers, etc. Conventional data center air conditioning units do not vary their cooling fluid output based on the distributed needs of the data center. Instead, these air conditioning units generally operate at or near a maximum compressor power even when the heat load is reduced inside the data center.
The substantially continuous operation of the air conditioning units is generally designed to operate according to a worst-case scenario. For example, air conditioning systems are typically designed around the maximum capacity and redundancies are utilized so that the data center may remain on-line on a substantially continual basis. However, the computer systems in the data center may only utilize around 30–50% of the maximum cooling capacity. In this respect, conventional cooling systems often attempt to cool components that may not be operating at a level which may cause their temperatures to exceed a predetermined temperature range. Consequently, conventional cooling systems often incur greater amounts of operating expenses than may be necessary to sufficiently cool the heat generating components contained in the racks of data centers.
Another problem associated with the cooling of data centers involves the expense and difficulty in measuring the environmental conditions, e.g., temperature, humidity, air flow, etc., within and around the racks. Although it has been found that the use of temperature sensors, e.g., thermocouples, located at various locations throughout the data center has been a relatively accurate manner of detecting temperatures, this practice has also been found to be relatively restrictive due to the difficulty and costs associated with this implementation. By way of example, a large number of sensors typically must be implemented to adequately detect the environmental conditions throughout the data center.
In addition, when the racks or components of a data center are added or re-arranged, the locations of the sensors must also be moved or recalibrated. Since most conventional sensors are wired to a power source and to a network for transmitting information, the movement of the sensors may prove to be a relatively difficult task requiring a great deal of time and manual input.
One solution to reducing costs associated with deploying and maintaining a sensor network has been to substantially reduce the total number of sensors employed in the data center. In this regard, the sensors are positioned at relatively distant locations with respect to each other. One problem associated with reducing the number of sensors is that there may be areas in which the sensors are unable to obtain sensed data. For instance, it may be difficult or impossible for the sensors to obtain sensed data at locations substantially centrally located between sensors. Another problem with reducing the number of sensors is that it may be impossible to determine problem areas, e.g., hot spots, malfunctioning vents, etc., as these problem areas may not be within range of the sensors. In addition, even if one or more of the sensors were able to detect a condition, e.g., air flow temperature, from a problem area, the air flow temperature may have varied from the time the air flowed from the problem area to the sensor. Therefore, it may be difficult to obtain environmental condition information with substantial accuracy and coverage.